BACKGROUND AND AIMS: A high proportion of patients develop chronic kidney disease (CKD) after liver transplantation (LT). We aimed to develop clinical/protein models to predict future glomerular filtration rate (GFR) deterioration in this population. APPROACH AND RESULTS: In independent multicenter discovery (CTOT14) and single-center validation (BUMC) cohorts, we analyzed kidney injury proteins in serum/plasma samples at month 3 after LT in recipients with preserved GFR who demonstrated subsequent GFR deterioration versus preservation by year 1 and year 5 in the BUMC cohort. In CTOT14, we also examined correlations between serial protein levels and GFR over the first year. A month 3 predictive model was constructed from clinical and protein level variables using the CTOT14 cohort (n = 60). Levels of β-2 microglobulin and CD40 antigen and presence of hepatitis C virus (HCV) infection predicted early (year 1) GFR deterioration (area under the curve [AUC], 0.814). We observed excellent validation of this model (AUC, 0.801) in the BUMC cohort (n = 50) who had both early and late (year 5) GFR deterioration. At an optimal threshold, the model had the following performance characteristics in CTOT14 and BUMC, respectively: accuracy (0.75, 0.8), sensitivity (0.71, 0.67), specificity (0.78, 0.88), positive predictive value (0.74, 0.75), and negative predictive value (0.76, 0.82). In the serial CTOT14 analysis, several proteins, including β-2 microglobulin and CD40, correlated with GFR changes over the first year. CONCLUSIONS: We have validated a clinical/protein model (PRESERVE) that early after LT can predict future renal deterioration versus preservation with high accuracy. This model may help select recipients at higher risk for subsequent CKD for early, proactive renal sparing strategies.
BACKGROUND AND AIMS: A high proportion of patients develop chronic kidney disease (CKD) after liver transplantation (LT). We aimed to develop clinical/protein models to predict future glomerular filtration rate (GFR) deterioration in this population. APPROACH AND RESULTS: In independent multicenter discovery (CTOT14) and single-center validation (BUMC) cohorts, we analyzed kidney injury proteins in serum/plasma samples at month 3 after LT in recipients with preserved GFR who demonstrated subsequent GFR deterioration versus preservation by year 1 and year 5 in the BUMC cohort. In CTOT14, we also examined correlations between serial protein levels and GFR over the first year. A month 3 predictive model was constructed from clinical and protein level variables using the CTOT14 cohort (n = 60). Levels of β-2 microglobulin and CD40 antigen and presence of hepatitis C virus (HCV) infection predicted early (year 1) GFR deterioration (area under the curve [AUC], 0.814). We observed excellent validation of this model (AUC, 0.801) in the BUMC cohort (n = 50) who had both early and late (year 5) GFR deterioration. At an optimal threshold, the model had the following performance characteristics in CTOT14 and BUMC, respectively: accuracy (0.75, 0.8), sensitivity (0.71, 0.67), specificity (0.78, 0.88), positive predictive value (0.74, 0.75), and negative predictive value (0.76, 0.82). In the serial CTOT14 analysis, several proteins, including β-2 microglobulin and CD40, correlated with GFR changes over the first year. CONCLUSIONS: We have validated a clinical/protein model (PRESERVE) that early after LT can predict future renal deterioration versus preservation with high accuracy. This model may help select recipients at higher risk for subsequent CKD for early, proactive renal sparing strategies.
Authors: Norah A Terrault; Geoff W McCaughan; Michael P Curry; Edward Gane; Stefano Fagiuoli; James Y Y Fung; Kosh Agarwal; Les Lilly; Simone I Strasser; Kimberly A Brown; Adrian Gadano; Paul Y Kwo; Patrizia Burra; Didier Samuel; Michael Charlton; Mario G Pessoa; Marina Berenguer Journal: Transplantation Date: 2017-05 Impact factor: 4.939
Authors: Josh Levitsky; Elizabeth C Verna; Jacqueline G O'Leary; Natalie H Bzowej; Dilip K Moonka; Robert H Hyland; Sarah Arterburn; Hadas Dvory-Sobol; Diana M Brainard; John G McHutchison; Norah A Terrault Journal: N Engl J Med Date: 2016-11-24 Impact factor: 91.245
Authors: Michael Charlton; Gregory T Everson; Steven L Flamm; Princy Kumar; Charles Landis; Robert S Brown; Michael W Fried; Norah A Terrault; Jacqueline G O'Leary; Hugo E Vargas; Alexander Kuo; Eugene Schiff; Mark S Sulkowski; Richard Gilroy; Kymberly D Watt; Kimberly Brown; Paul Kwo; Surakit Pungpapong; Kevin M Korenblat; Andrew J Muir; Lewis Teperman; Robert J Fontana; Jill Denning; Sarah Arterburn; Hadas Dvory-Sobol; Theo Brandt-Sarif; Phillip S Pang; John G McHutchison; K Rajender Reddy; Nezam Afdhal Journal: Gastroenterology Date: 2015-05-15 Impact factor: 22.682
Authors: Akinlolu O Ojo; Philip J Held; Friedrich K Port; Robert A Wolfe; Alan B Leichtman; Eric W Young; Julie Arndorfer; Laura Christensen; Robert M Merion Journal: N Engl J Med Date: 2003-09-04 Impact factor: 91.245
Authors: P De Simone; F Nevens; L De Carlis; H J Metselaar; S Beckebaum; F Saliba; S Jonas; D Sudan; J Fung; L Fischer; C Duvoux; K D Chavin; B Koneru; M A Huang; W C Chapman; D Foltys; S Witte; H Jiang; J M Hexham; G Junge Journal: Am J Transplant Date: 2012-08-06 Impact factor: 8.086